As a result of technological improvements in the area of electronics and communication, control technology for complex motion systems has taken a clear direction toward a networked architecture. A networked solution utilizes multiple simple controllers, referred to as remote controllers, which are located close to the components subject to control, such as motors and other actuators, and are coordinated by a master controller through a communication network.
The networked architecture opens numerous challenges in the areas of the division of the controls intelligence between the master and remote controllers, implementation of advanced control algorithms, communication network utilization, synchronization of components driven by different remote controllers, handling of events associated with inputs on multiple remote controllers, such as capturing positions of multiple axes of motion, accommodating a human presence in the work space, and dealing with power loss situations.
The division of the controls intelligence between the master and remote controllers may vary from a fully centralized architecture, where all or a majority of the control algorithms run on the master controller, to a distributed solution, where control algorithms are implemented on substantially autonomous remote controllers.
The benefits of a highly centralized architecture include the ability to provide advanced control algorithms, which often require real-time information from multiple axes, such as multi-input-multi-output (MIMO) control, and can be conveniently implemented on the master controller. The remote controllers in such an architecture require comparatively low computational power and small amounts of on-board memory, allowing for a relatively simple and inexpensive design.
These advantages may be achieved at the cost of a relatively high utilization of the communication network due to intensive time-critical data exchange between the remote controllers and the master controller because the master controller is closing the control loops. These systems usually have limited scalability because the maximum number of axes is constrained by the computational power of the master controller as well as the bandwidth of the communication network. In addition, since the remote controllers may not have enough intelligence to autonomously support failure-related operations, such as performing a controlled stop of the respective motion axes in the case of a failure of the communication network, satisfactory control in the event of a failure may be problematic to achieve.
In contrast, control systems with distributed control algorithms, which close the control loops on the remote controllers, executing on trajectory information received from the master controller, utilize comparatively low network traffic and substantially less time-critical data that may be conveniently buffered at the remote controllers to improve the overall capacity margin of the communication network. This approach may provide desirable scalability of the control system since increasing the number of remote controllers for additional axes automatically increases the overall computational power available for execution of the control loops. Furthermore, the remote controllers, being capable of generating simple trajectories and running control algorithms, have enough intelligence to support failure-related operations, such as a controlled stop, in the case of a failure of the communication network.
However, the additional intelligence of the remote controllers in the distributed architecture requires more computational power and memory, which generally makes the remote controllers more expensive. Also, implementation of full MIMO control algorithms is problematic since the control algorithms running on one remote controller generally do not have real-time access to the states of the axes driven by other remote controllers.
Implementation of a networked control system is generally facilitated by using a communication network with the appropriate capabilities. The IEEE 1394 communication network, also known as FireWire, is based on a high-speed serial bus which was developed to provide the same services as modern parallel buses, but at a substantially lower cost. The IEEE 1394b-2002 amendment defines features and mechanisms that provide gigabit speed extensions in a backwards compatible fashion and detection of physical loops in the bus topology and their subsequent resolution by selective disabling of physical layer (PHY) ports. A lightweight IEEE 1394 protocol was developed for efficient asynchronous communication to electronic instrumentation and industrial control devices by the 1394 Trade Association. Referred to as the Instrument and Industrial Control Protocol (IICP), it uses a dual-duplex plug structure for transfer of data and command/control sequences in a flow-controlled manner.
Control systems for accurate and synchronized control of precision robots generally require a certain level of system integrity, that is, the control systems may require interlocks, fail safe mechanisms, mechanisms for maintaining a minimum 100% up time, mechanisms and techniques to avoid damage to products being produced, and mechanisms and techniques to accommodate a human presence in workspaces of the control system.
State-of-the-art electronics and computers that implement programmable systems with a specified level of integrity tend to be marketed to the high-end of industrial machinery and processes. These types of systems are generally applicable to more stringent categories, for example, EN954 Category 4 or IEC61508 SIL 3, and use high-end processors or embedded CPU's. These types of systems are generally expensive and have more capability than required for low-end machinery or systems requiring lower levels of integrity, such as Category 2 or 3.
A machine designer who wishes to implement an alternative solution to programmable integrity to avoid the added cost of the specialized high-end electronics is faced with an extremely complex task of making the electronics, network and software of a control system meet integrity requirements and obtaining regulatory authority or auditor approval. Another issue with the existing technology that implements a specified level of integrity is size and form-factors, which are unsuitable for integrity applications with stringent space constraints.
There is a need for a control system that has the advantages of both a centralized and distributed architecture, that is flexible and scalable, that synchronizes component operations, that accommodates power losses and human presence in a workspace of the components subject to control, and that provides required system integrity levels.